Codipilly, Don C.

INTRODUCTION: Endoscopic eradication therapy (EET) combining endoscopic resection (ER) with endoscopic mucosal resection (EMR) or endoscopic submucosal dissection (ESD) followed by ablation is the standard of care for the treatment of dysplastic Barrett's esophagus (BE). We have previously shown comparable rates of complete remission of intestinal metaplasia (CRIM) with both approaches. However, data comparing recurrence after CRIM are lacking. We compared rates of recurrence after CRIM with both techniques in a multicenter cohort. METHODS: Patients undergoing EET achieving CRIM at 3 academic institutions were included. Demographic and clinical data were abstracted. Outcomes included rates and predictors of any BE and dysplastic BE recurrence in the 2 groups. Cox-proportional hazards models and inverse probability treatment weighting (IPTW) analysis were used for analysis. RESULTS: A total of 621 patients (514 EMR and 107 ESD) achieving CRIM were included in the recurrence analysis. The incidence of any BE (15.7, 5.7 per 100 patient-years) and dysplastic BE recurrence (7.3, 5.3 per 100 patient-years) were comparable in the EMR and ESD groups, respectively. On multivariable analyses, the chances of BE recurrence were not influenced by ER technique (hazard ratio 0.87; 95% confidence interval 0.51–1.49; P = 0.62), which was also confirmed by IPTW analysis (ESD vs EMR: hazard ratio 0.98; 95% confidence interval 0.56–1.73; P = 0.94). BE length, lesion size, and history of cigarette smoking were independent predictors of BE recurrence. DISCUSSION: Patients with BE dysplasia/neoplasia achieving CRIM, initially treated with EMR/ablation, had comparable recurrence rates to ESD/ablation. Randomized trials are needed to confirm these outcomes between the 2 ER techniques.

INTRODUCTION: Screening for Barrett's esophagus (BE) is suggested in those with risk factors, but remains underutilized. BE/esophageal adenocarcinoma (EAC) risk prediction tools integrating multiple risk factors have been described. However, accuracy remains modest (area under the receiver-operating curve [AUROC] ≤0.7), and clinical implementation has been challenging. We aimed to develop machine learning (ML) BE/EAC risk prediction models from an electronic health record (EHR) database. METHODS: The Clinical Data Analytics Platform, a deidentified EHR database of 6 million Mayo Clinic patients, was used to predict BE and EAC risk. BE and EAC cases and controls were identified using International Classification of Diseases codes and augmented curation (natural language processing) techniques applied to clinical, endoscopy, laboratory, and pathology notes. Cases were propensity score matched to 5 independent randomly selected control groups. An ensemble transformer-based ML model architecture was used to develop predictive models. RESULTS: We identified 8,476 BE cases, 1,539 EAC cases, and 252,276 controls. The BE ML transformer model had an overall sensitivity, specificity, and AUROC of 76%, 76%, and 0.84, respectively. The EAC ML transformer model had an overall sensitivity, specificity, and AUROC of 84%, 70%, and 0.84, respectively. Predictors of BE and EAC included conventional risk factors and additional novel factors, such as coronary artery disease, serum triglycerides, and electrolytes. DISCUSSION: ML models developed on an EHR database can predict incident BE and EAC risk with improved accuracy compared with conventional risk factor-based risk scores. Such a model may enable effective implementation of a minimally invasive screening technology.

The gastric conduit is commonly created after esophagectomy to restore intestinal continuity. In this review, we discuss several complications that can arise and can be managed by a gastroenterologist. We highlight endoscopic management of anastomotic leaks and strictures. We also describe the work up and management of reflux disease, delayed gastric conduit emptying, and dumping syndrome, all of which can complicate short- and long-term outcomes in patients receiving a gastric conduit.

AbstractBackground:Esophageal adenocarcinoma is a lethal cancer with rising incidence. There are limited data in younger (<50 years) patients with esophageal adenocarcinoma. We aimed to assess time trends in the incidence and outcomes of “young-onset” esophageal adenocarcinoma using a population-based database.Methods:We queried the Surveillance, Epidemiology, and End Results 9 database to identify patients with esophageal adenocarcinoma between 1975 and 2015. Patients were stratified into three age strata: <50, 50 to 69, and ≥70 years. Staging was stratified as localized, regional, and distant. Trends in incidence, disease stage, and survival were assessed in three periods (1975–89, 1990–99, and 2000–2015). Univariate and multivariate models were created to identify predictors of mortality.Results:Esophageal adenocarcinoma incidence has increased in patients <50 years of age, with an annual percentage change of 2.9% (95% confidence interval, 1.4%–4.4%) from 1975 to 2015. Young-onset esophageal adenocarcinoma presented at more advanced stages (regional + distant) compared with older patients (84.9% vs. 67.3%; P < 0.01), with increasing proportion of advanced stages over the study period. These patients also experienced poorer 5-year esophageal adenocarcinoma–free survival compared with older patients (22.9%% vs. 29.6%; P < 0.01), although this finding was attenuated on stage-stratified analysis.Conclusions:Young-onset esophageal adenocarcinoma, while uncommon, is rising in incidence. Concerningly, the proportion of advanced disease continues to increase. Young-onset esophageal adenocarcinoma also presents at more advanced stages, resulting in poorer esophageal adenocarcinoma–free survival.Impact:Patients with esophageal adenocarcinoma younger than 50 years present at more advanced stages with higher esophageal adenocarcinoma–specific mortality compared with older peers. Current diagnostic and management strategies for young-onset esophageal adenocarcinoma may need to be reevaluated.